<mets:mets OBJID="eprint_10208" LABEL="Eprints Item" xsi:schemaLocation="http://www.loc.gov/METS/ http://www.loc.gov/standards/mets/mets.xsd http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-3.xsd" xmlns:mets="http://www.loc.gov/METS/" xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><mets:metsHdr CREATEDATE="2023-07-05T01:38:06Z"><mets:agent ROLE="CUSTODIAN" TYPE="ORGANIZATION"><mets:name>OAR@ICRISAT</mets:name></mets:agent></mets:metsHdr><mets:dmdSec ID="DMD_eprint_10208_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:titleInfo><mods:title>Using participatory modeling processes to identify sources of climate risk in West Africa</mods:title></mods:titleInfo><mods:name type="personal"><mods:namePart type="given">L</mods:namePart><mods:namePart type="family">Schmitt Olabisi</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">S</mods:namePart><mods:namePart type="family">Liverpool-Tasie</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">L</mods:namePart><mods:namePart type="family">Rivers</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">A</mods:namePart><mods:namePart type="family">Ligmann-Zielinska</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">J</mods:namePart><mods:namePart type="family">Du</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">R</mods:namePart><mods:namePart type="family">Denny</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">S</mods:namePart><mods:namePart type="family">Marquart-Pyatt</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">A</mods:namePart><mods:namePart type="family">Sidibe</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:abstract>Participatory modeling has been widely recognized in recent years as a powerful tool for dealing with risk and uncertainty. By incorporating multiple perspectives into the structure of a model, we hypothesize that sources of risk can be identified and analyzed more comprehensively compared to traditional ‘expert-driven’ models. However, one of the weaknesses of a participatory modeling process is that it is typically not feasible to involve more than a few dozen people in model creation, and valuable perspectives on sources of risk may therefore be absent. We sought to address this weakness by conducting parallel participatory modeling processes in three countries in West Africa with similar climates and smallholder agricultural systems, but widely differing political and cultural contexts. Stakeholders involved in the agricultural sector in Ghana, Mali, and Nigeria participated in either a scenario planning process or a causal loop diagramming process, in which they were asked about drivers of agricultural productivity and food security, and sources of risk, including climate risk, between the present and mid-century (2035–2050). Participants in all three workshops identified both direct and indirect sources of climate risk, as they interact with other critical drivers of agricultural systems change, such as water availability, political investment in agriculture, and land availability. We conclude that participatory systems methods are a valuable addition to the suite of methodologies for analyzing climate risk and that scientists and policy-makers would do well to consider dynamic interactions between drivers of risk when assessing the resilience of agricultural systems to climate change.</mods:abstract><mods:classification authority="lcc">Climate Risk</mods:classification><mods:classification authority="lcc">Participatory Modeling</mods:classification><mods:classification authority="lcc">Climate Change</mods:classification><mods:classification authority="lcc">Food Security</mods:classification><mods:classification authority="lcc">African Agriculture</mods:classification><mods:classification authority="lcc">West Africa</mods:classification><mods:originInfo><mods:dateIssued encoding="iso8061">2017-10</mods:dateIssued></mods:originInfo><mods:originInfo><mods:publisher>Springer</mods:publisher></mods:originInfo><mods:genre>Article</mods:genre></mets:xmlData></mets:mdWrap></mets:dmdSec><mets:amdSec ID="TMD_eprint_10208"><mets:rightsMD ID="rights_eprint_10208_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:useAndReproduction>
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